Given that agricultural research depends basically on data and analysis, governmental agencies, publishers and science funders now require data management plans for publicly funded experiments. This, along with the sheer volume of agricultural biological data being produced today makes good data management essential.

In 2015, AgBioData - a consortium of agricultural biological databases - was formed to identify common goals relating to data set acquisition, display, user retrieval and manipulation; data (storage and sharing), software and hardware standards, and database best practices that would have the most efficient impact on agriculture (research) agendas, through more efficient database solutions.

2.) to encourage authentic, detailed, accurate and explicit communication and sharing among databases of agricultural data in order to identify common problems and collaborate on solving them, as well as to avoid duplication of work and support small research groups,

As a step toward these goals, the AgriBioData Team presents the current state of biocuration, ontologies, metadata and persistence, database platforms, programmatic (machine) access to data, communication and sustainability with regard to data curation:

1.) to document the current challenges and opportunities of GGB (genomic, genetic and breeding) databases and online resources regarding the collection, integration and provision of data in a standardized way;

2.) to outline a set of standards and best practices for GGB databases and their curators;

3.) to inform policy and decision makers about the growing importance of scientific data curation and management to the research community.

The publication is divided into seven sections and each section contains an (i) Overview, (ii) Challenges and (iii) Recommendations.